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Metaverse is a concept that envisions a future where the physical and digital worlds merge to form a shared space for people to experience and interact with each other. This research aims to study the underlying factors (functional, psychological and individual barriers) that build resistance toward metaverse among tourists. The study has used innovation resistance theory (IRT) to make the conceptual model. The study used a mixed-method approach to investigate the proposed model, with data collected from 26 tourists for qualitative analysis and 198 for quantitative analysis. The data were analysed using structural equation modelling for path analysis. For moderation, the study used process macro model no. 1. The study results showed that the use of metaverse experiences requires certain conditions that increase the cost of usage. Technology vulnerability, characterized by dependence on technology and anxiety about it, was identified as the main cause of innovation resistance also found that people who are not inclined to be innovative or inventive are less likely to embrace new technology and access to better resources, compatible devices, and user-friendly environments can help reduce the barriers that users face in adopting metaverse applications. Tourism, which is mainly related to pleasure and happiness, is strongly influenced by hedonic motivations.

AbstractThe rise of cord-cutting due to technological advancements and internet accessibility has led to an increased interest in understanding the adoption behavior of consumers towards over-the-top services (OTTs). This study aimed to comprehend the barriers to adopting the first wave of OTTs and the innovation characteristics, along with the propagation mechanism, in the second wave, using the Innovation Resistance Theory (IRT) and the Technology Acceptance Model (TAM), respectively. The study was conducted in India, with 302 and 572 respondents for the first and second waves, respectively. Data were analyzed through confirmatory factor analysis and structural equation modeling. The findings revealed that value barriers, technology vulnerability barriers, and individual barriers had the highest impact on consumer resistance, negatively impacting continued usage intention. Consumer habits were found to play a conditional role in antagonizing the effects of consumer resistance on continued usage intention. In the second wave, innovation and consumer characteristics had no significant impact on continued usage behavior. Instead, a robust propagation mechanism was explored to overcome consumer resistance and promote innovation. These findings provide valuable insights for OTT service providers and policymakers to promote continued usage intention and overcome consumer resistance.